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62.000.151 Documentos en la biblioteca con la clasificación 62.000.285 (1)
Crear una solicitud de compra Refinar búsquedaBig Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach / Hassanien, Aboul-Ella ; Dey, Nilanjan ; Elghamrawy, Sally
TÃtulo : Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach Tipo de documento: documento electrónico Autores: Hassanien, Aboul-Ella, ; Dey, Nilanjan, ; Elghamrawy, Sally, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2020 Número de páginas: XI, 307 p. 169 ilustraciones, 130 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-55258-9 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: IngenierÃa Inteligencia artificial Inteligencia Computacional IngenierÃa Biomédica EpidemiologÃa Grandes datos IngenierÃa de datos IngenierÃa Biomédica y BioingenierÃa Clasificación: 62.000.285 Resumen: Este libro incluye artÃculos de investigación y artÃculos expositivos sobre las aplicaciones de la inteligencia artificial y el análisis de big data para combatir la pandemia. En el contexto de la COVID-19, este libro se centra en cómo el análisis de big data y la inteligencia artificial ayudan a combatir la COVID-19. El libro está dividido en cuatro partes. La primera parte analiza la previsión y visualización de los datos de COVID-19. La segunda parte describe las aplicaciones de la inteligencia artificial en el diagnóstico de COVID-19 mediante radiografÃas de tórax. La tercera parte analiza los conocimientos de la inteligencia artificial para detener la propagación de la COVID-19, mientras que la última parte presenta el aprendizaje profundo y el análisis de big data que ayudan a combatir la COVID-19. . Nota de contenido: Coronavirus Spreading Forecasts based on Susceptible-Infectious- Recovered and Linear Regression Model -- Virus Graph and COVID-19 Pandemic: A Graph Theory Approach -- Nonparametric Analysis of Tracking Data in the Context of COVID-19 Pandemic -- Visualization and prediction of trends of Covid-19 pandemic during early outbreak in India using DNN and SVR -- The Detection of COVID-19 in CT Medical Images: A Deep Learning Approach -- COVID-19 Data Analysis and Innovative approach in Prediction of Cases -- Detection of COVID-19 using Chest Radiographs with Intelligent Deployment Architecture -- COVID-19 Diagnostics from the Chest X-Ray Image Using Corner-Based Weber Local Descriptor -- Why are Generative Adversarial Networks Vital for Deep Neural Networks? A Case Study on COVID-19 Chest X-Ray Images -- Artificial intelligence against COVID-19: A meta-analysis of current research -- Insights of Artificial Intelligence to Stop Spread of COVID-19 -- AI based Covid19 analysis-A pragmatic approach -- Artificial Intelligence and Psychosocial Support during the COVID-19 Outbreak -- Role of The Accurate Detection of Core Body Temperature in The Early Detection of Coronavirus -- The effect Coronavirus Pendamic on Education into Electronic Multi-Modal Smart Education -- An H2O's Deep Learning-inspired model based on Big Data analytics for Coronavirus Disease (COVID-19) Diagnosis -- Coronavirus (COVID-19) Classification using Deep Features Fusion and Ranking Technique -- Stacking Deep Learning for Early COVID-19 Vision Diagnosis. Tipo de medio : Computadora Summary : This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19. . Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach [documento electrónico] / Hassanien, Aboul-Ella, ; Dey, Nilanjan, ; Elghamrawy, Sally, . - 1 ed. . - [s.l.] : Springer, 2020 . - XI, 307 p. 169 ilustraciones, 130 ilustraciones en color.
ISBN : 978-3-030-55258-9
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: IngenierÃa Inteligencia artificial Inteligencia Computacional IngenierÃa Biomédica EpidemiologÃa Grandes datos IngenierÃa de datos IngenierÃa Biomédica y BioingenierÃa Clasificación: 62.000.285 Resumen: Este libro incluye artÃculos de investigación y artÃculos expositivos sobre las aplicaciones de la inteligencia artificial y el análisis de big data para combatir la pandemia. En el contexto de la COVID-19, este libro se centra en cómo el análisis de big data y la inteligencia artificial ayudan a combatir la COVID-19. El libro está dividido en cuatro partes. La primera parte analiza la previsión y visualización de los datos de COVID-19. La segunda parte describe las aplicaciones de la inteligencia artificial en el diagnóstico de COVID-19 mediante radiografÃas de tórax. La tercera parte analiza los conocimientos de la inteligencia artificial para detener la propagación de la COVID-19, mientras que la última parte presenta el aprendizaje profundo y el análisis de big data que ayudan a combatir la COVID-19. . Nota de contenido: Coronavirus Spreading Forecasts based on Susceptible-Infectious- Recovered and Linear Regression Model -- Virus Graph and COVID-19 Pandemic: A Graph Theory Approach -- Nonparametric Analysis of Tracking Data in the Context of COVID-19 Pandemic -- Visualization and prediction of trends of Covid-19 pandemic during early outbreak in India using DNN and SVR -- The Detection of COVID-19 in CT Medical Images: A Deep Learning Approach -- COVID-19 Data Analysis and Innovative approach in Prediction of Cases -- Detection of COVID-19 using Chest Radiographs with Intelligent Deployment Architecture -- COVID-19 Diagnostics from the Chest X-Ray Image Using Corner-Based Weber Local Descriptor -- Why are Generative Adversarial Networks Vital for Deep Neural Networks? A Case Study on COVID-19 Chest X-Ray Images -- Artificial intelligence against COVID-19: A meta-analysis of current research -- Insights of Artificial Intelligence to Stop Spread of COVID-19 -- AI based Covid19 analysis-A pragmatic approach -- Artificial Intelligence and Psychosocial Support during the COVID-19 Outbreak -- Role of The Accurate Detection of Core Body Temperature in The Early Detection of Coronavirus -- The effect Coronavirus Pendamic on Education into Electronic Multi-Modal Smart Education -- An H2O's Deep Learning-inspired model based on Big Data analytics for Coronavirus Disease (COVID-19) Diagnosis -- Coronavirus (COVID-19) Classification using Deep Features Fusion and Ranking Technique -- Stacking Deep Learning for Early COVID-19 Vision Diagnosis. Tipo de medio : Computadora Summary : This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19. . Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
